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Mendeley readers
Attention Score in Context
| Title |
The use of the Gail model, body mass index and SNPs to predict breast cancer among women with abnormal (BI-RADS 4) mammograms
|
|---|---|
| Published in |
Breast Cancer Research, January 2015
|
| DOI | 10.1186/s13058-014-0509-4 |
| Pubmed ID | |
| Authors |
Anne Marie McCarthy, Brad Keller, Despina Kontos, Leigh Boghossian, Erin McGuire, Mirar Bristol, Jinbo Chen, Susan Domchek, Katrina Armstrong |
| Abstract |
IntroductionMammography screening results in a significant number of false-positives. The use of pre-test breast cancer risk factors to guide follow-up of abnormal mammograms could improve the positive predictive value of screening. We evaluated the use of the Gail model, body mass index (BMI), and genetic markers to predict cancer diagnosis among women with abnormal mammograms. We also examined the extent to which pre-test risk factors could reclassify women without cancer below the biopsy threshold.MethodsWe recruited a prospective cohort of women referred to biopsy with abnormal (BI-RADS 4) mammograms. Breast cancer risk factors were assessed prior to biopsy. A validated panel of 12 single nucleotide polymorphisms (SNPs) associated with breast cancer were measured. Logistic regression was used to assess the association of Gail risk factors, BMI and SNPs with cancer diagnosis (invasive or DCIS). Model discrimination was assessed using area under the receiver operating curve and calibration was assessed using the Hosmer-Lemeshow goodness of fit test. Finally, the distribution of predicted probabilities of cancer diagnosis were compared for women with and without breast cancer.ResultsIn the multivariate model, age (OR¿=¿1.05, 95% CI 1.03 to 1.08 P <0.001), SNP panel relative risk (OR¿=¿2.30, 95% CI 1.06 to 4.99, P¿=¿0.035), and BMI (¿30 kg/m2 versus <25 kg/m2, OR¿=¿2.20, 95% CI 1.05 to 4.58, P¿=¿0.036) were significantly associated with breast cancer diagnosis. Older women were more likely to be diagnosed with breast cancer. The SNP Panel RR remained strongly associated with breast cancer diagnosis after multivariable adjustment. Higher BMI was also strongly associated with increased odds of breast cancer diagnosis. Obese women (OR¿=¿2.20, 95% CI 1.05 to 4.58, P¿=¿0.036) had more than twice the odds of cancer diagnosis compared to women with BMI <25 kg/m2. The SNP Panel appeared to have predictive ability among both white and black women.ConclusionsBreast cancer risk factors, including BMI and genetic markers are predictive of cancer diagnosis among women with BI-RADS 4 mammograms. Using pre-test risk factors to guide follow-up of abnormal mammograms could reduce the burden of false-positive mammograms. |
X Demographics
The data shown below were collected from the profiles of 4 X users who shared this research output. Click here to find out more about how the information was compiled.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Spain | 1 | 25% |
| United Kingdom | 1 | 25% |
| Unknown | 2 | 50% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Members of the public | 3 | 75% |
| Science communicators (journalists, bloggers, editors) | 1 | 25% |
Mendeley readers
The data shown below were compiled from readership statistics for 53 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| United Kingdom | 1 | 2% |
| Unknown | 52 | 98% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Researcher | 12 | 23% |
| Student > Ph. D. Student | 8 | 15% |
| Student > Master | 5 | 9% |
| Professor > Associate Professor | 4 | 8% |
| Student > Bachelor | 2 | 4% |
| Other | 5 | 9% |
| Unknown | 17 | 32% |
| Readers by discipline | Count | As % |
|---|---|---|
| Medicine and Dentistry | 14 | 26% |
| Biochemistry, Genetics and Molecular Biology | 5 | 9% |
| Agricultural and Biological Sciences | 5 | 9% |
| Nursing and Health Professions | 3 | 6% |
| Psychology | 2 | 4% |
| Other | 8 | 15% |
| Unknown | 16 | 30% |
Attention Score in Context
This research output has an Altmetric Attention Score of 2. This is our high-level measure of the quality and quantity of online attention that it has received. This Attention Score, as well as the ranking and number of research outputs shown below, was calculated when the research output was last mentioned on 03 February 2015.
All research outputs
#15,740,207
of 25,374,647 outputs
Outputs from Breast Cancer Research
#1,387
of 2,053 outputs
Outputs of similar age
#193,894
of 358,875 outputs
Outputs of similar age from Breast Cancer Research
#32
of 52 outputs
Altmetric has tracked 25,374,647 research outputs across all sources so far. This one is in the 37th percentile – i.e., 37% of other outputs scored the same or lower than it.
So far Altmetric has tracked 2,053 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 12.2. This one is in the 30th percentile – i.e., 30% of its peers scored the same or lower than it.
Older research outputs will score higher simply because they've had more time to accumulate mentions. To account for age we can compare this Altmetric Attention Score to the 358,875 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 44th percentile – i.e., 44% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 52 others from the same source and published within six weeks on either side of this one. This one is in the 36th percentile – i.e., 36% of its contemporaries scored the same or lower than it.